13 Chapter 8: Interviews

If you’re conducting qualitative research, interviews are one of the most powerful tools at your disposal. Unlike surveys or observations, which can only capture what people do, interviews allow you to explore why they do it uncovering thoughts, emotions, and perspectives that remain hidden in other research methods (Merriam, 2009). The decision to use interviews depends largely on what kind of information you need and how deeply you want to understand your participants’ experiences.

DeMarrais (2004) defines an interview as “a process in which a researcher and participant engage in a conversation focused on questions related to a research study” (p. 55, cited in Merriam, 2009). Interviews are particularly useful when you need to understand an individual’s perspective, what Patton (2002) describes as capturing the participant’s unique viewpoint. This aligns with the emic perspective introduced by Bickman and Rog (2009), which emphasizes how people interpret their own realities rather than how researchers define them from an external standpoint. While quantitative research often aims for generalizability, qualitative interviews allow you to delve into personal narratives, emotions, and reflections, offering a richer and more nuanced understanding of your research topic.

As Patton (2002) explains:

“We interview people to find out from them those things we cannot directly observe [. . . . ] We cannot observe feelings, thoughts, and intentions. We cannot observe behaviors that took place at some previous point in time. We cannot observe situations that preclude the presence of an observer. We cannot observe how people have organized the world and the meanings they attach to what goes on in the world. We have to ask people questions about those things. The purpose of interviewing, then, is to allow us to enter into the other person’s perspective” (pp. 340–341, cited in Merriam, 2009, p. 88).

This is why interviews are invaluable when trying to capture deeply personal or reflective data, insights that would be impossible to obtain through observation alone (Merriam, 2009). As Merriam (2009) points out, interviews are especially useful when you’re trying to gather information that is otherwise inaccessible such as personal reflections, subjective viewpoints, or historical events that cannot be replicated. If your research involves exploring how people think, feel, and make sense of their experiences, then interviews provide you with a unique window into their world.

In this chapter, we explore the role of interviews in qualitative research, highlighting their value in uncovering rich, in-depth insights that other methods often miss. We begin by discussing the unique strengths of interviews and the theoretical foundations that support their use. We then outline the different types of interviews, structured, semistructured, and unstructured as well as focus groups emphasizing when and why each approach might be appropriate.

The chapter also examines various modes of conducting interviews, including face-to-face, videoconferencing, and telephone interviews, along with their respective advantages and limitations. A significant portion is dedicated to how AI tools can support interview preparation, transcription, and data management, offering practical strategies and tool recommendations. Finally, We conclude with guidance on refining AI-generated transcripts and ensuring ethical practices around data security and participant validation.

I. Interview Types

Merriam (2009, p. 89) categorizes interviews into three main types based on their level of structure. The choice of interview type depends on the research objectives, the degree of flexibility required, and the nature of the data being collected.

1. Structured Interviews

Structured interviews follow a predetermined set of questions with fixed wording and order, resembling an oral survey. This format ensures consistency across participants, making it particularly useful in quantitative research where comparability is key. Structured interviews are commonly used to collect demographic data, such as age, education, and employment status, as seen in U.S. Census Bureau surveys and market research studies.

2. Semistructured Interviews

Semistructured interviews use a flexible interview guide that includes both structured and open-ended questions. While specific data is required from all participants, the wording and sequence of questions may be adjusted to allow for deeper exploration of responses. This approach balances consistency with adaptability. Researchers can probe further based on participants’ answers to  uncover insights that structured interviews might not elicit.

3. Unstructured/Informal Interviews

Unstructured interviews are open-ended, conversational, and exploratory. Without a rigid set of questions, these interviews allow participants to freely express their thoughts. This type is especially valuable in ethnographic research, participant observation, and case studies where little is known about a topic beforehand. The flexibility of unstructured interviews enables researchers to adapt their inquiries as themes emerge and thus ensure a richer, more organic exploration of the subject matter.

While individual interviews allow for deep, personalized insights, there are times when the interaction between participants adds another valuable layer of understanding. In such cases, focus groups provide a powerful alternative.

Focus groups

Interviews in qualitative research can take different forms, ranging from one-on-one conversations to group discussions. While individual interviews allow for deep, personal insights, group settings can offer something equally valuable, the dynamics of interaction. In some cases, the interplay of ideas, shared experiences, and collective meaning-making are just as important as individual responses. This is where focus groups come in handy.

Focus groups have become a widely used method in qualitative research because they tap into the power of group interaction to generate rich, layered data. As Kitzinger (1995) explains:

“Focus groups are a form of group interview that capitalizes on communication between research participants in order to generate data. Although group interviews are often used simply as a quick and convenient way to collect data from several people simultaneously, focus groups explicitly use group interaction as part of the method. This means that instead of the researcher asking each person to respond to a question in turn, people are encouraged to talk to one another: asking questions, exchanging anecdotes and commenting on each other’s experiences and points of view.” (p. 299)

Unlike a series of individual responses collected in a group setting, focus groups capture the natural flow of conversation, how participants build on, challenge, or reshape each other’s ideas. If your goal is to explore shared experiences, cultural norms, or how people make sense of complex issues, then focus groups are an excellent choice. Robinson (1999) describes them as structured discussions with small groups typically 5 to 8 participants engaging in conversations that often reveal insights you wouldn’t get from one-on-one interviews. This makes them especially useful in researching sensitive topics or exploring how opinions evolve in a group context. They’re widely used in healthcare and social research to understand patient experiences, assess public attitudes, or evaluate the impact of policies and interventions.

II- Modes of Conducting Interviews

As a researcher, you have several options for conducting interviews, depending on your study’s needs, accessibility, and convenience. The traditional face-to-face interview is still one of the most widely used methods; one that allows you to observe what participants say and how they say it through facial expressions, tone, and body language. But what if meeting in person isn’t possible? That’s where technology steps in. You can conduct interviews through video recordings, videoconferencing, or even telephone calls, each offering unique advantages and challenges.

1. Video recorded face to face interviews

Recording your interviews on video is a powerful way to capture richer data that you would not normally capture using only audio recordings. With video, you’re not just collecting spoken words, you’re also capturing facial expressions, gestures, and body language, all of which add layers of meaning that might otherwise be missed. A participant’s tone of voice might suggest hesitation, their posture could indicate discomfort, or their facial expressions might reveal emotions that contradict their verbal responses. These nonverbal cues provide deeper insights that can help you interpret responses with greater accuracy.

Beyond offering more nuanced data, video recordings also reduce the risk of misinterpretation. Instead of relying solely on memory or incomplete notes, you can revisit the footage multiple times to ensure a more precise analysis. Even better, video interviews allow for multi-analyst review, meaning multiple researchers can independently analyze the footage increasing reliability and reducing bias.

That said, video recording interviews comes with its own set of challenges, and you’ll need to navigate them carefully. Some participants may feel uncomfortable being on camera which can result in more guarded responses. To ease their concerns, it’s essential to obtain informed consent, clearly explain how the recordings will be used, and reassure them about confidentiality.

Another challenge is the resource-intensive nature of video interviews. Unlike audio recordings, video files are larger and require secure storage solutions. Transcription and analysis also take more time, and you’ll need reliable equipment to ensure high-quality recordings. Then there’s researcher influence. Participants might become self-conscious and adjust their responses to appear more socially acceptable rather than offer their most natural thoughts. And, of course, technical issues can get in the way. Poor lighting, background noise, or a badly positioned camera can compromise your data; so it’s worth testing your setup in advance to ensure clear and usable footage. Despite these challenges, video-recorded interviews remain one of the most effective tools for capturing rich, detailed qualitative data.

2. Videoconferencing

While video recording in face-to-face settings enhances data collection, video conferencing has revolutionized how researchers conduct interviews. With the increasing accessibility of digital tools, platforms like Zoom, Skype, and Microsoft Teams allow you to conduct interviews, focus groups, and discussions with participants from anywhere in the world. This can be a major advantage especially if you’re studying dispersed or hard-to-reach populations. Videoconferencing saves money, too: no travel costs, no need to rent a space, and scheduling is often more flexible for both you and your participants. Plus, there’s something about being in one’s own environment that tends to make people open up more, which can really enrich the data you collect.

That said, videoconferencing does have its own challenges and limitations. Tech issues like poor internet, video lag, or garbled audio can easily disrupt an interview. Even small delays can throw off the rhythm of a conversation and cause awkward overlaps or silences that complicate transcription and analysis later. And while video gives you more to work with than audio alone, it still doesn’t fully capture all the nuances of body language, which can be critical in sensitive interviews.

Ethics is another big piece of the puzzle. Just because you can hit “record” doesn’t mean you should, at least not without clear, informed consent. It’s important to explain how the recording will be used, stored, and protected. You may need to rely on verbal consent or digital forms instead of signed papers, and not all platforms are equally secure. So, if you’re dealing with sensitive data, make sure you’re using a tool that offers good encryption and store your recordings safely preferably offline. Also, be prepared for a few more no-shows than you’d expect in face-to-face settings. Since it’s easier for people to cancel or forget an online meeting, this can impact your schedule and potentially reduce your sample size. It’s not a dealbreaker, but it’s something worth factoring into your planning.

3. Telephone Interviews

If you’re considering telephone interviews for your research, don’t think of them as a second-best option to video or face-to-face formats. In fact, they offer some distinct advantages that can actually enhance the quality of your data. For one, people tend to feel more comfortable and less self-conscious when they’re not being watched. This can be especially helpful when you’re exploring personal or sensitive topics. Participants might open up more when they don’t feel the pressure of being visually observed. That sense of distance, ironically, can create a safe space for honesty.

Telephone interviews are also incredibly flexible. Your participants can speak with you from any quiet space that works for them, which is ideal if they’re juggling responsibilities or live in remote locations. That autonomy can make them more relaxed and willing to share. And if you’re interviewing someone with limited internet access or less comfort with video platforms, the phone might just be the best fit.

Still, phone interviews come with their own set of challenges. Without visual cues, you’ll need to be more intentional about how you listen and respond. Verbal affirmations, those little “mm-hmms” and “that’s interesting”, go a long way in showing you’re engaged and encouraging participants to keep talking. Since your tone and pacing are doing all the work, you’ll want to be especially mindful of how you guide the conversation and when to pause, prompt, or follow up.

On the ethical side, even though there’s no camera involved, informed consent is still critical. You’ll need to clearly explain everything whether you’re recording the call, how the data will be stored, and that participants can opt out at any time. For topics that are emotionally heavy or deeply personal, the voice-only format may help people feel more anonymous and secure, but it also means you need to be extra attentive to signs of distress and be ready to provide support if needed. So, while phone interviews may seem simple on the surface, they require a thoughtful and responsive approach to be truly effective.

III- Using AI in Interviews

In this section, we discuss the different ways we can leverage the power of AI to help us conduct better interviews. Most of the tips and tools and guidelines will work for different types of interviews including face to face, video conferencing, or telephone interviews. However, before conducting an interview, you need to carefully plan your questions and AI-powered tools such as AI chatbots can help a lot in this phase. You can use these tools to generate, refine, and improve your interview questions.

Here are few tips to help you get optimal results in this regard. First, provide the chatbot with contextual information about your interview and upload guidelines if you have any. The more context the chatbot has, the more relevant and precise its suggestions will be. For example, let’s say you’re researching college students’ use of AI in their studies and preparing to interview a student. Here’s a sample prompt you might use:

“Based on the best practices I shared with you and considering the topic of my research [provide research context], I need help formulating research questions for my interview. Can you suggest a list of open-ended questions that encourage in-depth responses?”

Once the chatbot generates a list, review the output carefully. Ask follow-up questions, request iterations, and refine until you’re satisfied with the final set of questions. AI isn’t perfect, but by going through multiple iterations, you can ensure your questions are clear, inclusive, and free from bias.

Another helpful way to use AI chatbots to help with preparing for your interviews is create simulations. The chatbot can act as a participant allowing you to practice your questioning techniques and refine phrasing. You can even Use ChatGPT’s voice mode which can make the interaction feel even more realistic.

For example, you can say:

“I will ask you a series of interview questions. Please answer as if you were a college student discussing your experiences with AI in education. Try to provide detailed responses.”

After running the simulation, evaluate how the conversation flowed. Did any questions feel unclear? Did some answers seem too surface-level? Use this feedback to fine-tune your interview questions before moving forward.

If you already have a set of interview questions, whether ones you’ve drafted yourself or ones that emerged from your research, you can still use AI to improve them. For instance, you can ask the chatbot to review your questions for clarity and conciseness and request suggestions for more inclusive and unbiased language. For example, you might say:

“Here is my list of interview questions: [paste questions]. Can you review them and suggest improvements to enhance clarity and inclusivity?”

AI can also help you structure the interview itself. You can ask it to generate a tentative script, including:

• A professional introduction: How to greet participants and establish rapport.
• Smooth transitions: How to move naturally from one topic to the next.
• A strong conclusion: How to wrap up the interview while leaving room for additional insights.

For instance, here is a sample prompt to use in this regard:

“Can you draft a structured interview guide that includes an introduction, transitions between sections, and a closing statement? The topic is [insert research topic], and the interview format is [face-to-face/video/telephone].”

Once AI provides a script, review and refine it to ensure it aligns with your research style and objectives. Next, we’ll explore how AI can assist in transcription turning your recorded interviews into accurate, searchable text for analysis.

Transcribing interviews

Transcribing interview data has traditionally been one of the most time-consuming and exhausting tasks in qualitative research. For years, researchers like us, who couldn’t afford costly transcription software, had no choice but to painstakingly transcribe interviews manually. But now, AI-powered speech-to-text tools have transformed transcription into an efficient, near-instantaneous process. Instead of spending hours meticulously typing out interviews, you can now upload an audio file and receive a transcript within minutes.

In the next section, we share a collection of recommendations for speech-to-text tools that can help streamline your research workflow but before that here are few things to keep in mind.

If you’re using video conferencing tools like Google Meet, Zoom, or Microsoft Teams for your interviews, they do offer built-in transcription features. However, these tools are fairly basic when it comes to transcription (Zalani, 2024). You won’t get advanced meeting insights, the ability to take structured notes, or options to highlight and share specific meeting clips. But if all you need is a straightforward transcript of what was said, they can certainly get the job done. Here’s how they compare:

While Zoom, Google Meet, and Microsoft Teams remain powerful platforms that offer transcription services, there are now a wide variety of AI-powered tools that offer much more than simple transcription. These tools can transcribe your audio, tag key themes, identify speaker turns, summarize interviews, and generate insights or action points. Some allow you to search by keyword, create visual timelines of conversations, and export transcripts in formats that are compatible with qualitative analysis software.

This evolution means transcription is no longer limited to converting audio into text. It can now help you structure, organize, and interpret your data more efficiently. As a researcher, this can significantly reduce the time you spend processing interviews while giving you more meaningful and accessible material for your analysis.

Here is a curated list of AI transcription tools that can support this enhanced workflow.

1. Rev AI

Rev AI is a powerful AI-driven speech-to-text tool that can help you transcribe your interviews with speed and accuracy. Rev AI can handle both audio and video files. Simply upload your file (Rev supports various files including MP3, MP4, WMV, AVI and more), provide your email and your completed transcript will be emailed to you once ready. If you need real-time transcription, Rev AI also offers streaming transcription which allows you to transcribe audio or video as it’s streamed. And in case you don’t want AI to do the transcription, you can opt for human-created transcription as well with a 24-hour turnaround time (English only).

Besides basic transcription services, Rev AI offers powerful AI-driven features to help you analyze your interview data more efficiently. For instance, Rev AI’s sentiment analysis can automatically detect positive, negative, or neutral statements in your interviews (English only). This is especially useful when analyzing participant attitudes, emotional tones, or overall perceptions without having to manually label responses. If you’re conducting interviews on sensitive topics or consumer feedback research, this feature can help you quickly identify patterns in how people feel about specific issues.

Another powerful tool is topic extraction, which automatically highlights key themes in your interview transcripts. Rev AI can tag relevant topics based on your content which makes it easier to organize and categorize responses. This is useful for qualitative research where patterns and themes emerge across multiple interviews. Need a concise summary of your interviews? Rev AI’s summarization feature converts long-form spoken content into brief, actionable summaries. This can help you quickly grasp the main points of a discussion without reading through the entire transcript thus saving time when reviewing multiple interviews.

2. Otter AI

Otter AI is another robust AI-powered speech to text tool to help you transcribe the data of your interviews. It works with both audio and video files and can be used whether you’re conducting face-to-face interviews (with recordings), video conferencing interviews, or even transcribing podcasts and lectures.

Getting started is simple: you can use Otter’s mobile app, desktop browser, or Chrome/Firefox extensions to record and transcribe interviews instantly. If you’ve already conducted an interview and need a transcript, just upload your audio or video file, and Otter AI will generate a transcript for you. All your transcripts are neatly stored in the My Conversations tab where you can review, edit, and organize them for later use.

One of the features I like about Otter AI is its AI-powered assistant, OtterPilot. If you’re conducting video conferencing interviews on Zoom, Google Meet, or Microsoft Teams, OtterPilot can automatically join the meeting, transcribe in real-time, and even generate summaries. You don’t need to take notes while interviewing, Otter captures everything for you allowing you to stay fully engaged with your participant. Even better, if any slides or screen shares are presented during the discussion, OtterPilot automatically adds them to the meeting notes.

For interview analysis, Otter AI provides speaker identification to help you keep track of who said what. You can also highlight key takeaways, tag specific parts of the transcript, and assign action items within your notes. Searching through transcripts is effortless thanks to advanced search and playback options. You can quickly locate important moments without scrolling through pages of text. Otter can identify key themes, sentiment, and important points within conversations.

3. Descript

Descript is another AI-powered option to consider when dealing with audio and video transcriptions. It offers a full-fledged platform that helps you manage, edit, and analyze recorded interview data with ease. With automatic transcription, speaker labeling, and AI-driven summarization, Descript streamlines the entire transcription process allowing you to focus on analyzing your interviews rather than getting stuck with manual note-taking.

Descript’s AI-powered transcription supports 23 languages. If you’re dealing with multiple interviewees, the built-in speaker labeling automatically identifies different voices in your recording which helps you track who said what. You can import your files by dragging and dropping them into the platform, and if your recording is particularly long, Descript can handle large files, though for best performance, longer files (over 15 hours) are split into manageable segments.

And like previous tools, Descript provides access to different AI-powered analysis features. For instance, Dewcript can summarize key insights and help you quickly extract main ideas without combing through hours of text. Its AI-powered Chapter Generator automatically adds chapter markers enabling you to easily navigate lengthy interviews. If you need to highlight important moments, Descript’s Find Good Clips feature scans your recording and identifies the best snippets, a helpful feature when you’re pulling quotes or key excerpts for analysis.

Another feature that makes Descript incredibly useful for research is text-based editing. Once your interview is transcribed, you can edit the text and it will automatically adjust the corresponding audio or video. This means that if you find errors or filler words in the transcript, you can remove them just like editing a text document thus saving you time in cleaning up your data. If there are redundant sections, Descript’s Remove feature automatically detects and deletes unnecessary re-recorded part. For remote interviews conducted over Zoom, Descript integrates directly with the platform allowing you to import and transcribe Zoom recordings effortlessly.

Other notable transcription tools:

4. Sonix

Sonix is a versatile AI-powered transcription tool that supports both audio and video files.  Some of its main features include:

• AI-powered speech-to-text transcription in 53+ languages
• Fast, automated transcription with speaker identification
• Real-time transcription for immediate text generation
• AI-generated summaries & topic detection for quick insights
• Automated chapter creation to structure long interviews
• Advanced search to find key phrases easily
• Topic & entity detection – Identify key themes and topics
• Translation into 54+ languages for multilingual research
• Secure, encrypted storage for sensitive data
• Seamless integration with Zoom, Google Meet, and MS Teams

5. Riverside AI

Riverside offers AI-powered transcription for both audio and video recordings. Key features in Riverside AI include:

• AI-driven transcription with near-perfect accuracy
• Supports over 100 languages, accents, and regional dialects
• Automatic speaker detection for multi-person interviews
• Real-time transcription as soon as recording is complete
• Edit audio and video by modifying the transcript
• Records in high-quality 4K video and clear audio

6. TurboScribe AI

TurboScribe is an AI-powered transcription tool that converts audio and video interviews into text. Main features provided include:

• Fast transcription for both audio and video files
• High accuracy with AI-powered speech recognition
• Speaker labeling for multi-participant interviews
• Supports 98+ languages with translation to 134+ languages
• Secure, private, and encrypted storage for sensitive data
• Export transcripts in multiple formats, including PDF, DOCX, and SRT

7. Notta AI

Notta converts audio and video content into text and supports 58 languages. Key Features:

• Convert audio and video into accurate text effortlessly.
• Transcribe in 58 languages and translate into 40+ with a single click.
• Automatically labels speakers in conversations for easy reference.
• Edit transcripts within Notta and export them in various formats like PDF, DOCX, and SRT.
• Upload files from YouTube, Google Drive, Dropbox, and more for seamless transcription.
• Generate key takeaways from long transcripts in seconds.

8. Happy Scribe

Happy Scribe is another powerful video-to-text transcription that offers numerous features including:

• Choose between fast, automated AI transcription .
• Transcribe videos in over 120 languages, dialects, and accents.
• Upload files from your device, Google Drive, YouTube, Dropbox, and more.
• Edit and fine-tune transcripts with an interactive text editor.
• Download transcripts in TXT, DOCX, PDF, and more.
• Convert transcripts into subtitles for accessibility and video content enhancement.

Working with AI-Generated Transcripts

Now that you have your interview transcripts, the next step is to prepare them for analysis. While we won’t go into the details of data analysis here (that’s covered in the AI for Data Analysis chapter), we want to share some practical strategies to help you refine, organize, and optimize your transcripts before moving forward.

AI-generated transcripts can be a huge time-saver, but they still require careful review and formatting. Ensuring accuracy, improving readability, and annotating key insights are all small yet crucial steps that make your transcripts more reliable and easier to analyze. Some of the AI transcription tools mentioned earlier also integrate basic analysis features helping with tasks like speaker identification, keyword extraction, and sentiment analysis. The following are some practical tips to keep in mind as you work with your AI-generated transcripts:

1. Review for Accuracy

Once your transcript is generated, don’t assume it’s perfect. Go through it manually to catch any errors. AI transcription tools, while powerful, can still misinterpret speech, misspell names, or mislabel speakers, especially when dealing with accents, technical jargon, or overlapping dialogue. A quick skim won’t be enough, take the time to carefully review and refine the text to ensure accuracy. Look out for slip-ups, filler words, repeated lines, and incorrect punctuation. Pay extra attention to names, specialized terminology, and critical statements, as these are often misrepresented by AI. If your tool provides speaker attribution, double-check that each section is assigned to the correct person.

2. Enhance Readability of the Transcript

Many AI transcription tools now offer features like speaker identification, timestamps, and automatic paragraph structuring, but you shouldn’t rely on them blindly. Go through your transcript carefully and ensure that everything is labeled correctly. Misattributed dialogue or missing timestamps can lead to confusion later when you’re trying to track who said what. A clear structure makes your transcript more navigable and allows you to quickly locate important sections. Consider adding consistent paragraph breaks, adjusting line spacing, and ensuring that each speaker is properly labeled. This is especially important for focus groups or multi-participant interviews, where distinguishing between speakers is crucial. Investing a little time in cleaning up the formatting now will save you a lot of frustration when you move on to analysis.

3. Annotate your Transcripts

Annotating your transcripts is one of the best ways to actively engage with your data before diving into analysis. Instead of just reading through pages of text, adding comments, highlights, and summaries helps you interact with the material at a deeper level. It allows you to spot key themes, track emerging patterns, and flag important moments that might otherwise get lost in the sheer volume of data. Many AI transcription tools now include built-in annotation features, making this process even more efficient. You can use AI to generate summaries, extract key insights, and even highlight recurring topics all of which help you organize your data more effectively.

A good practice is to highlight meaningful quotes that you might want to reference in your findings. Adding brief notes or reflections next to these sections can help you recall why they stood out. When comparing across multiple interviews, these annotations act as quick reference points allowing you to trace connections between different participants’ perspectives without re-reading entire transcripts. The more structured your annotations, the easier it will be to transition into the analysis phase later

4. Secure your Data

One of the most important yet often overlooked aspects of working with interview transcripts is data security. You’ve put in the time and effort to conduct interviews, transcribe them, and prepare them for analysis, now you need to ensure that your data is protected. A single technical failure, accidental deletion, or security breach can cost you hours of work and valuable research insights. That’s why it’s crucial to have a solid backup strategy in place.

A good rule of thumb is to store your data in multiple locations. We suggest that you  always save your research data both in the cloud (e.g., Google Drive, Dropbox, or OneDrive) and locally on your computer. For extra security, you can keep an additional copy on an external hard drive. This way, if something happens, whether it’s a device crash, accidental deletion, or a lost password, you still have access to your files. You might also consider using encrypted storage solutions if you’re handling sensitive data.

Beyond backup strategies, don’t forget about ethical responsibilities and data protection policies. If your research involves confidential or personally identifiable information, anonymize transcripts before storing or sharing them. Remove names, locations, or any other details that could compromise participant privacy. Always follow institutional guidelines and legal requirements related to data storage and protection. Taking these extra precautions ensures that your hard work remains safe, accessible, and ethically managed throughout your research process.

5. Sharing Transcripts with Interviewees

After transcribing your interviews, you might consider sharing the transcripts with participants for validation. Mero-Jaffe (2011) discusses how this practice, often called member checking, can enhance trust and accuracy in qualitative research. By allowing participants to review their words, you give them an opportunity to clarify, expand, or correct any misinterpretations. This can be particularly useful for ensuring that complex ideas, cultural nuances, or emotional expressions are accurately represented. However, while this process strengthens ethical transparency, it can also introduce complications, as participants may refine their speech and make it more structured or formal than what was originally expressed.

One challenge noted by Mero-Jaffe (2011) is the power shift that occurs when participants are given control over transcripts. Some may delete important content, modify responses to sound more articulate, or even regret certain statements they initially shared. This can lead to a loss of spontaneity and authenticity in the data. Additionally, not all participants are comfortable reviewing transcripts, and some may choose not to engage with the process at all. As a researcher, it’s important to weigh the benefits and drawbacks of transcript sharing carefully to ensure that it aligns with the goals of your study while maintaining the integrity of participant voices.

 Conclusion

Interviews are one of the most powerful ways to understand how people think, feel, and make sense of their experiences. Talking directly with participants gives you access to stories and insights you simply can’t get through other methods. In this chapter, we looked at different types of interviews and how each one can serve a different purpose, depending on what you’re trying to learn. We also explored the various ways you can conduct interviews (i.e., face-to-face, over video, or by phone) and how each method brings its own set of strengths and challenges. Finally, we saw how AI tools can support you at every stage of the process, from preparing questions to transcribing and organizing your data.  In the next chapter, we’ll take a closer look at surveys as another important method for gathering data.